Manal Farhan Mohsin AL-Khakani

Accurate and early diagnosis of osteoporosis, a skeletal disorder characterized by low bone density and increased fracture risk, is crucial for effective management. This study aimed to evaluate the diagnostic potential of adiponectin and leptin levels as biomarkers for osteoporosis. Objectives: The primary objective of this study was to investigate whether adiponectin and leptin levels could serve as biomarkers for diagnosing osteoporosis and distinguishing it from healthy individuals. Materials and Methods: Abstract Background: Accurate and early diagnosis of osteoporosis, a skeletal disorder characterized by low bone density and increased fracture risk, is crucial for effective management. This study aimed to evaluate the diagnostic potential of adiponectin and leptin levels as biomarkers for osteoporosis. Objectives: The primary objective of this study was to investigate whether adiponectin and leptin levels could serve as biomarkers for diagnosing osteoporosis and distinguishing it from healthy individuals. Materials and Methods: A total of ninety participants, including healthy individuals (n = 30) and patients with osteoporosis (n = 30) or osteopenia (n = 30), underwent comprehensive evaluations. Demographic, clinical, hormonal, and lipid profiles were assessed. Additionally, bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry. Enzyme-linked immunosorbent assays were conducted to measure adiponectin and leptin levels in serum samples. Results: Significant differences were observed between osteoporosis patients and healthy controls in several parameters. Osteoporosis patients were older and had a lower body mass index compared to healthy individuals. Furthermore, BMD was significantly lower in osteoporosis patients. Hormonal and lipid profiles also differed significantly between the two groups. Notably, adiponectin levels were lower, whereas leptin levels were higher in osteoporosis patients compared to healthy controls. These findings suggest that adiponectin and leptin levels may have diagnostic potential for osteoporosis. Conclusion: Adiponectin and leptin levels exhibit promise as biomarkers for the accurate diagnosis of osteoporosis and differentiation from healthy individuals. Further research and validation studies are warranted to confirm their utility in clinical practice.

Abstract Background: Chronic kidney disease (CKD) is a rapidly expanding public health problem typified by either an increased excretion of albumin in the urine, a reduced glomerular filtration rate, or both. Copeptin is formed by the breakdown of arginine vasopressin precursor (AVP), produced in the hypothalamus in an equimolar ratio and processed during axonal transport. AVP is an unstable peptide with a short half-life of five to twenty minutes. Compared to AVP, copeptin is a stable molecule that is simple to test. Objective: This study aims to determine whether plasma copeptin is a helpful biomarker for predicting chronic renal disease and the relationship between copeptin and certain electrolytes. Materials and Methods: This research involved a case–control study involving 88 participants, 44 individuals diagnosed with CKD, and 44 apparently healthy individuals serving as the control group. Blood samples were collected to measure copeptin, calcium, potassium, and sodium. Other variables, including age and body mass index (BMI), were also assessed. BMI was calculated by dividing weight in kilograms by height in meters squared. Statistical analyses, including Pearson correlation and receiver operating characteristic curve analysis, were conducted to evaluate the diagnostic accuracy of copeptin. Results: This study found that the copeptin concentration in the patient group increased significantly (p ˂ 0.05) compared to the control group, and the area under the curve for copeptin was 0.994. Conclusion: The results emphasize that copeptin plays a crucial role in CKD.

Abstract Objectives: The present study aims to show:1- Evaluation of serum (Phosphorus, Calcium, Magnesium, Zinc, and Iron) in patients under study and compare with controls group. 2- Radiological finding and its significance in diagnosing of osteoporosis. DEXA is the essential indicative decision by which to screen women >50 years of age for osteoporosis; Evaluation variation of T-scores. Methods: Serum Calcium and other measured were compared between the patients group (122) and controls (32), The patients were determined to have osteoporosis as DEXA check. Results: Comparison between patients and controls group; Serum calcium was a significant decrease in postmenopausal women (osteoporosis) when compared to postmenopausal women (healthy) ; Serum phosphorus, serum magnesium, serum iron, and serum zinc between two groups were a significant decrease in postmenopausal women (osteoporosis); T-scores were a significant decrease in postmenopausal women osteoporosis group, compared to controls group. Conclusions: Serum calcium, phosphorus, magnesium, iron and zinc levels in postmenopausal women, these metals were found to have a significant relationship with the controls group and were almost as low or normal. It was considered to be essential in diagnosis and detection. Diagnosis of osteoporosis disease in postmenopausal women by DEXA is the right choice for detection by using as T-scores.

Abstract Osteoporosis are an absolutes decline in mass of bone tissue. bestow to be a most public health problem .for they are associated with increase mortality and morbidity especially vertebral and hip fracture, which are a huge burden on the health system required to the high financial cost of this care fracture. The aim of research is to estimation the correlation between colony stimulating factor1 and progesterone from postmenopausal women ; the comparison of each parameters between osteoporosis in postmenopausal women and postmenopausal women without osteoporosis. Serum CSF1 and progesterone measured biochemical parameters were compared between the patients (140) and healthy (40). The significantly high concentration of progesterone and T-scores in patients with osteoporosis compared with the control group, and no significantly concentration of CSF1 in patients with osteoporosis compared with the control group Serum CSF1 were positively correlated (p =0.032) with(progesterone) for osteoporotic groups ,and negatively correlated(p=0.984) with progesterone for control groups. Progesterone levels can be predicted significantly using the most correlated with CSF1 Keywords: 0steoporosis, CSF1, M-CSF, progesterone

Osteoporosis is group of those diseases which affect elderly people especially women. They have adverse effects on person and economic burden on society, because of their side effects especially hip fractures. Each year many women with those disease mainly those with osteoporosis are exposed to incidents of fracture. These incidents are merely resulting from falling or simple reasons such as the acts of bending or coughing as in the case with the vertebral fracture. Therefore, it is crucial to identify those people who are at risk, from the very early stages of such diseases. Macrophage colony stimulating factor (M-CSF) is a member of the family of proteins referred to as colony stimulating factors(CSFs).M-CSF is a secreted or a cell surface glycoprotein comprised of two subunits that are joined by a disulfide bond with a total molecular mass varying from 40 to 90 kD. Similar to other CSFs, M-CSF is produced by macrophages, monocytes, and human joint tissue cells,. M-CSF-related disease states include osteoporosis, in which monocytes/macrophages and related cell types play a role. For instance, osteoclasts are similar to macrophages and are regulated in part by M-CSF. Postmenopausal bone loss results from defective bone remodeling secondary to an uncoupling of bone formation from exuberant osteoclast mediated bone resorption as a consequence of estrogen deficiency. Multinuclear osteoclast formation induced by (M-CSF + RANKL ) is completely abrogated by treatment with GM-CSF. In the present study, the correlation of M-csf and GM-CSF level with Bone mineral densityand Estrogen was investigated to determine the factors that mainly affect M-CSF correlation in patients with osteoporosis. M-CSF and other measured biochemical parameters were compared between the patients (122) and healthy (32). Serum (M-CSF) and (GM-CSF) were positively correlated (p < 0.0001) with Estrogen, and negatively(p < 0.001) correlated with BMD. GM-CSF was correlated with M-CSF. showed a significant difference between osteoporotic and control groups. Estrogen and bone mineral density (BMD) levels can be predicted significantly using the most correlated with M-csf and GM-csf Keywords: 0steoporosis, M-CSF,GM-CSF ,BMD, Estrogen.

Abstract Background. Hepcidin is a master regulator of iron metabolism that inhibits the transport of iron out of enterocytes and macrophages. Thalassemia major (TM) is associated with some of the endocrine disorders. However, studies have yet to be conducted on the correlation of hepcidin with hormone levels and insulin resistance (IR) in patients with TM. Objectives. In the present study, the correlation of hepcidin level with some endocrine and biochemical parameters was investigated to determine the factors that mainly affect hepcidin correlation in patients with thalassemia. These factors include hormones, iron status, and IR parameters. Material and Methods. Hepcidin and other measured biochemical parameters were compared between the TM patients (100) and healthy children (37). Results. Serum thyroid-stimulating hormone (TSH) was positively correlated (p < 0.05) with hepcidin, iron, and ferritin. T4 hormone was correlated with ferritin only. Other hormones showed different correlation patterns with iron status parameters but were statistically insignificant (p > 0.05). The percentage of ƒÀ-cell function was the only parameter among the IR parameters that showed a significant difference between thalassemic and control groups. Conclusions. Thyroid and ƒÀ-cells dysfunctions are common in TM patients with frequent blood transfusions. In addition, hepcidin and TSH levels can be predicted significantly using the most correlated factors with hepcidin. These factors, including ferritin, insulin and TSH were used to construct predicting equations: S. Hepcidin = = 0.003*Ferritin + 3.02*TSH + 0.12*Insulin + 16.85 (} 7.78) and TSH = 0.0083 ~ Insulin + 0.0042 ~ Ferritin + + 0.0937 ~ Hepcidin + 1.91 (} 1.373) (Adv Clin Exp Med 2015, 24, 1, 69.78).